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Robust Deconvolution of Underwater Acoustic Channels Corrupted by Impulsive Noise

Cang, Siyuan LU ; Sheng, Xueli ; Jakobsson, Andreas LU orcid and Yang, Huayong (2022) 5th International Conference on Information Communication and Signal Processing, ICICSP 2022 p.571-576
Abstract

Impulsive noise is one of the most challenging forms of interference in an underwater acoustic environment. In this paper, we present an underwater acoustic channel deconvolution method based on a sparse representation framework. The application of the method enables a channel impulse response reconstruction that is robust to impulsive noise. By exploiting the inherent structure in the channel response, the measured signal may be expressed as depending on the unknown channel in a multiplicative manner, enabling an efficient deconvolution framework. This allow us introduce an lp-norm optimization framework that is then adopted to deconvoluting the under-water acoustic channel in the presence of impulsive noise. The resulting framework is... (More)

Impulsive noise is one of the most challenging forms of interference in an underwater acoustic environment. In this paper, we present an underwater acoustic channel deconvolution method based on a sparse representation framework. The application of the method enables a channel impulse response reconstruction that is robust to impulsive noise. By exploiting the inherent structure in the channel response, the measured signal may be expressed as depending on the unknown channel in a multiplicative manner, enabling an efficient deconvolution framework. This allow us introduce an lp-norm optimization framework that is then adopted to deconvoluting the under-water acoustic channel in the presence of impulsive noise. The resulting framework is efficiently solved using the alternating direction method of multipliers (ADMM). The performance of the proposed algorithm is demonstrated using simulations and experimental data collected from South China Sea.

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Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
ADMM, Impulsive Noise, Robust Deconvolution, Underwater
host publication
2022 5th International Conference on Information Communication and Signal Processing, ICICSP 2022
pages
6 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
5th International Conference on Information Communication and Signal Processing, ICICSP 2022
conference location
Shenzhen, China
conference dates
2022-11-26 - 2022-11-28
external identifiers
  • scopus:85149960951
ISBN
9781665485890
DOI
10.1109/ICICSP55539.2022.10050612
language
English
LU publication?
yes
id
81eb46e5-f704-4a6b-84c8-7b9a791686dd
date added to LUP
2023-04-03 13:50:09
date last changed
2023-11-21 06:10:29
@inproceedings{81eb46e5-f704-4a6b-84c8-7b9a791686dd,
  abstract     = {{<p>Impulsive noise is one of the most challenging forms of interference in an underwater acoustic environment. In this paper, we present an underwater acoustic channel deconvolution method based on a sparse representation framework. The application of the method enables a channel impulse response reconstruction that is robust to impulsive noise. By exploiting the inherent structure in the channel response, the measured signal may be expressed as depending on the unknown channel in a multiplicative manner, enabling an efficient deconvolution framework. This allow us introduce an lp-norm optimization framework that is then adopted to deconvoluting the under-water acoustic channel in the presence of impulsive noise. The resulting framework is efficiently solved using the alternating direction method of multipliers (ADMM). The performance of the proposed algorithm is demonstrated using simulations and experimental data collected from South China Sea.</p>}},
  author       = {{Cang, Siyuan and Sheng, Xueli and Jakobsson, Andreas and Yang, Huayong}},
  booktitle    = {{2022 5th International Conference on Information Communication and Signal Processing, ICICSP 2022}},
  isbn         = {{9781665485890}},
  keywords     = {{ADMM; Impulsive Noise; Robust Deconvolution; Underwater}},
  language     = {{eng}},
  pages        = {{571--576}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Robust Deconvolution of Underwater Acoustic Channels Corrupted by Impulsive Noise}},
  url          = {{http://dx.doi.org/10.1109/ICICSP55539.2022.10050612}},
  doi          = {{10.1109/ICICSP55539.2022.10050612}},
  year         = {{2022}},
}